An excellent Machine Learning Engineer (MLOps / AI Platform) opportunity has just arisen within a cutting-edge AI environment.
Job Purpose:
- Build and scale machine learning systems from experimentation to reliable production deployment.
Job Responsibilities:
- Design and deploy machine learning solutions from data pipelines to production systems.
- Build scalable pipelines for training, testing, and serving AI models reliably.
- Work with data scientists to convert research code into production-ready applications.
- Manage model lifecycle including versioning, monitoring, performance tracking, and continuous improvements.
- Implement modern AI solutions including LLMs, agents, and retrieval-based systems.
Job Requirements:
- 7+ years Python programming experience building scalable and maintainable applications.
- Experience deploying machine learning models into production environments using modern tools.
- Familiarity with cloud platforms, containers, and CI/CD pipelines for automation.
- Understanding of machine learning concepts, data processing, and model evaluation techniques.
- Experience or interest in LLMs, AI agents, or modern generative AI technologies.
The successful Machine Learning Engineer (MLOps / AI Platform) must possess strong Python skills, production ML experience, and interest in modern AI technologies such as LLMs and automation workflows.
Work on real-world AI systems including LLMs, automation workflows, and scalable ML platforms.
EA Reg. No. 25C2690 | EA license No. R1330510
